Plain-English Glossary

Prompt

The instruction you give a tool so it knows what you want.

Why it matters

Better prompts usually mean less cleanup and fewer weird detours.

Context

The extra background an AI tool gets before it answers.

Why it matters

Without context, even a smart tool starts guessing.

Workflow

A repeatable sequence of steps that gets a job done.

Why it matters

The goal is not magic. The goal is a process you can actually use again.

Automation

Getting a tool to handle repetitive steps for you.

Why it matters

It saves time, reduces boredom, and frees up attention for the part that still needs taste.

Agent

An AI tool that can do more than answer a question, like take steps or use other tools.

Why it matters

This is where AI starts behaving more like a helper than a chatbot.

MCP

A way for AI tools to connect to files, apps, and outside systems.

Why it matters

It turns a detached assistant into something that can actually participate in your workflow.

RAG

A system that lets AI pull in relevant documents or notes before answering.

Why it matters

It helps the model work from your information instead of just its built-in memory.

Embeddings

A way of turning text into coordinates so a computer can find similar ideas.

Why it matters

They power better search, retrieval, and memory systems.

Hallucination

When an AI tool makes something up and says it confidently.

Why it matters

You still need judgment. The machine can sound sure and still be wrong.

Prototype

A rough first version used to test an idea before polishing it.

Why it matters

It is often the fastest way to find out if an idea deserves more time.

Iteration

Trying, adjusting, and refining in small loops.

Why it matters

Most useful work comes from repetition, not one perfect pass.

Vector Search

A way of finding related ideas by meaning instead of exact wording.

Why it matters

It helps note systems and AI helpers find the right material faster.